A Review of Performance, Energy and Privacy of Intrusion Detection Systems for IoT

Arshad, Junaid; Azad, Muhammad Ajmal; Amad, Roohi; Alazab, Mamoun

doi:10.3390/electronics9040629

Cited by 62 publications

(39 citation statements)

References 73 publications

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“…In addition, they only selected 131 articles for review. Most of the review studies not listed in Table 2 focused on specific areas of IoT security, such as layer protocols [33], intrusion detection [34], device security [35,36], trust [37], and security of specific IoT applications [38]. us, a systematic mapping study is still required to determine research topics and trends in IoT security and gain insights on this field.…”

Section: Comparison With Related Reviewsmentioning

confidence: 99%

Current Research Trends in IoT Security: A Systematic Mapping Study

Lee

2021

Mobile Information Systems

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The smart mobile Internet-of-things (IoT) network lays the foundation of the fourth industrial revolution, the era of hyperconnectivity, hyperintelligence, and hyperconvergence. As this revolution gains momentum, the security of smart mobile IoT networks becomes an essential research topic. This study aimed to provide comprehensive insights on IoT security. To this end, we conducted a systematic mapping study of the literature to identify evolving trends in IoT security and determine research subjects. We reviewed the literature from January 2009 to August 2020 to identify influential researchers and trends of keywords. We additionally performed structural topic modeling to identify current research topics and the most promising ones via topic trend estimation. We synthesized and interpreted the results of the systematic mapping study to devise future research directions. The results obtained from this study are useful to understand current trends in IoT security and provide insights into research and development of IoT security.

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Section: Comparison With Related Reviewsmentioning

confidence: 99%

Current Research Trends in IoT Security: A Systematic Mapping Study

Lee

2021

Mobile Information Systems

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“…The intrusion detection system (IDS) is required to prevent unauthorized access to IoT. [153]. But these introduce challenges to power, bandwidth, and network.…”

Section: Mitigationsmentioning

confidence: 99%

Decades of Internet of Things towards 21st Century: A Research-Based Introspective

Boobalakrishnan¹

2021

Preprint

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Internet connects people to people, people to machine, and machine to machine for a life of serendipity through a Cloud. Internet of Things networks objects or people and integrates them with software to collect and exchange data. The Internet of things (IoT) influences our lives based on how we ruminate, respond, and anticipate. IoT 2020 heralds from the fringes to the data ecosystem and panaches a comfort zone. IoT is overwhelmingly embraced by businessmen and consumers due to increased productivity and convenience. Internet of Things facilitates intelligent device control with cloud vendors like Amazon and Google using artificial intelligence for data analytics, and with digital assistants like Alexa and Siri providing a voice user interface. Smart IoT is all about duplex connecting, processing, and implementing. With 5G, lightning faster rate of streaming analytics is realistic. An amalgamation of technologies has led to this techno-industrial IoT revolution. Centralized IoT architecture is vulnerable to cyber-attacks. With Block Chain, it is possible to maintain transparency and security of the transaction's data. Standardization of IoT devices is achievable with limited vendors based on Platform, Connectivity, and Application. Robotic Process Automation (RPA) using bots has automated laborious tasks in 2019. Embedded Internet using Facial Recognition could reduce the pandemic crisis. Security concerns are addressed with micro-segmentation approaches. IoT, an incredible vision of the future makes systems adaptive with customized features, responsive with increased efficiency, and procurable with optimized cost. This paper delivers a comprehensive insight into the technical perspectives of IoT, focusing on interoperability, flexibility, scalability, mobility, security, transparency, standardization, and low energy.

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“…On the other hand, anomaly-based IDS find anomalous behavior by learning from current data. Therefore, they can detect new attacks, but they are less accurate and computationally expensive (Arshad et al 2020;Jan et al 2019;Midi et al 2017). The recent attacks such as DoS, DDoS and different malware attacks are the most common mitigated attacks by IDSs (Din et al 2019;Meidan et al 2018;Roopak et al 2020).…”

Section: Intrusion and Malware Detectionmentioning

confidence: 99%

Peer Review #1 of "A systematic review of security and privacy issues in the internet of medical things; the role of machine learning approaches (v0.1)"

2021

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Background . The Internet of Medical Things (IoMTs) is gradually replacing the traditional healthcare system. However, little attention has been paid to their security requirements in the development of the IoMT devices and systems. One of the main reasons can be the difficulty of tuning conventional security solutions to the IoMT system. Machine Learning (ML) has been successfully employed in the attack detection and mitigation process. Advanced ML technique can also be a promising approach to address the existing and anticipated IoMT security and privacy issues. However, because of the existing challenges of IoMT system, it is imperative to know how these techniques can be effectively utilized to meet the security and privacy requirements without affecting the IoMT systems quality, services, and device's lifespan.Methodology. This paper is devoted to perform a Systematic Literature Review (SLR) on the security and privacy issues of IoMT and their solutions by ML techniques. The recent research papers disseminated between 2010 to 2020 are selected from multiple databases and a standardized SLR method is conducted. A total of 153 papers were reviewed and a critical analysis were conducted on the selected papers. Furthermore, this review study attempts to highlight the limitation of the current methods and aims to find possible solutions to them. Thus, a detailed analysis was carried out on the selected papers through focusing on their methods, advantages, limitations, the utilized tools, and data. Results.It was observed that ML techniques have been significantly deployed for device and network layer security. Most of the current studies improved traditional metrics while ignored performance complexity metrics in their evaluations. Their studies environments and utilized data barely represent IoMT system. Therefore, conventional ML techniques may fail if metrics such as resource complexity and power usage are not considered.

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A Review of Performance, Energy and Privacy of Intrusion Detection Systems for IoT

Cited by 62 publications

References 73 publications

Current Research Trends in IoT Security: A Systematic Mapping Study

Current Research Trends in IoT Security: A Systematic Mapping Study

Decades of Internet of Things towards 21st Century: A Research-Based Introspective

Peer Review #1 of "A systematic review of security and privacy issues in the internet of medical things; the role of machine learning approaches (v0.1)"

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